Appendix I. Recent Studies of Inflation in Russia, Ukraine, Belarus and Moldova
Appendix II. Recent Cross-Country Studies on Inflation.
Appendix III. Data
Appendix IV. Data Correlation Matrices
Appendix V. Robustness of Econometric Results
Aisen, Ari, and Francisco Jose Veiga, 2006. Does Political Instability Lead to Higher Inflation? A Panel Data Analysis. Journal of Money, Credit, and Banking Vol. 38, No. 5, pp. 1379-90.
Arellano, Manuel, and Stephen Bond, 1991. Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations. Review of Economic Studies Vol. 58, No. 2, pp. 277-97.
Barro, Robert J., and David B. Gordon, 1983. A Positive Theory of Monetary Policy in a Natural Rate Model. Journal of Political Economy Vol. 91, No. 4, pp. 589-610.
Bassett, Sheila, 2003. The Feasibility of Inflation Targeting in Ukraine. IMF Country Report No. 03/173, pp. 37-48, International Monetary Fund.
Beck, Nathaniel, and Jonathan N. Katz, 1995. What to Do (and not to Do) with Time-Series Cross-Section Data. American Political Science Review Vol. 89, No. 3, pp. 634-47.
Blundell, Richard, and Stephen Bond, 1998. Initial Conditions and Moment Restrictions in Dynamic Panel Data Models. Journal of Econometrics Vol. 87, No. 1, pp. 115-43.
Boskin, Michael J., Ellen R. Dulberger, Robert J. Gordon, Zvi Griliches, and Dale W. Jorgenson, 1996. Toward a More Accurate Measure of the Cost of Living. Final Report to the U.S. Senate Finance Committee from the Advisory Commission to study the Consumer Price Index.
- Search Google Scholar
- Export Citation
)| false Boskin, Michael J., Ellen R. Dulberger, Robert J. Gordon, Zvi Griliches, and Dale W. Jorgenson, 1996. Toward a More Accurate Measure of the Cost of Living. Final Report to the U.S. Senate Finance Committee from the Advisory Commission to study the Consumer Price Index.
Boskin, Michael J., Ellen R. Dulberger, Robert J. Gordon, Zvi Griliches, and Dale W. Jorgenson, 1998. Consumer Prices, the Consumer Price Index, and the Cost of Living. Journal of Economic Perspectives Vol. 12, No. 1, pp. 3-26.
Brachinger, Hans Wolfgang, Bernd Schips, and Winfried Stier, 1999. Expertise zur Relevanz des “Boskin-Reports” für den schweizerischen Landesindex der Konsumentenpreise. Bundesamt für Statistik, Neuchatel, Switzerland.
Cottarelli, Carlo, Mark Griffiths, and Reza Moghadam, 1998. The Nonmonetary Determinants of Inflation: A Panel Data Study. IMF Working Papers 98/23, International Monetary Fund.
Cukierman, Alex, Sebastian Edwards, and Guido Tabellini, 1992. Seigniorage and Political Instability. American Economic Review Vol. 82, No. 3, pp. 537-55.
Cukierman, Alex, Geoffrey P. Miller, and Bilin Neyapti, 2002. Central Bank Reform, Liberalization and Inflation in Transition Economies—an International Perspective. Journal of Monetary Economics Vol. 49, No. 2, pp. 237-64.
Cunningham, Alastair, 1996. Measurement Bias in Price Indices: An Application to the UK’s RPI. Bank of England Working Paper Series 47, Bank of England.
Diewert, Erwin W., 1997. Comment. In: T. Bresnahan and R. J. Gordon (eds.), The Economics of New Goods. University of Chicago Press. Chicago, pp. 423-33.
Égert, Balázs, 2005. Equilibrium Exchange Rates in South-Eastern Europe, Russia, Ukraine and Turkey: Healthy or (Dutch) Diseased? Economic Systems Vol. 29, No. 2, pp. 205-41.
Égert, Balázs, László Halpern, and Ronald MacDonald, 2006. Equilibrium Exchange Rates in Transition Economies: Taking Stock of the Issues. Journal of Economic Surveys Vol. 20, No. 2, pp. 257-324.
Filer, Randall K., and Jan Hanousek, 2000. Output Changes and Inflationary Bias in Transition. Economic Systems Vol. 24, No. 3, pp. 285-94.
Filer, Randall K., and Jan Hanousek, 2003. Inflationary Bias in Middle to Late Transition Czech Republic. Economic Systems Vol. 27, No. 4, pp. 367-76.
Granville, Brigitte, and Sushanta Mallick, 2006. Monetary Policy in Russia. Chapter 4 in: Lúcio Vinhas de Souza and Oleh Havrylyshyn (eds.), Growth Resumption in the CIS. Elsevier. Amsterdam, Netherlands.
Hoffmann, Johannes, 1999. Problems of Inflation Measurement in Germany: An Update. Mimeo. Eurostat Conference, Cardiff, U.K., September 1999.
IMF, 2005a. Republic of Belarus: Report on the Observance of Standards and Codes—Data Module, Response by the Authorities, and Detailed Assessments Using the Data Quality Assessment Framework. IMF Country Report No. 05/29, International Monetary Fund.
IMF, 2005b. Republic of Belarus: 2005 Article IV Consultation—Staff Report. IMF Country Report No. 05/214, International Monetary Fund.
IMF, 2005c. Ukraine: 2005 Article IV Consultation and Ex Post Assessment of Longer-Term Program Engagement—Staff Reports. IMF Country Report No. 05/415, International Monetary Fund.
IMF, 2006. Republic of Belarus: 2006 Article IV Consultation—Staff Report. IMF Country Report No. 06/314, International Monetary Fund.
Ivanova, Anna, Michael Keen, and Alexander Klemm, 2005. The Russian ‘Flat Tax’ Reform. Economic Policy Vol. 20, No. 43, pp. 397-444.
Leheyda, Nina, 2006. Determinants of Inflation in Ukraine: A Cointegration Approach. In Lúcio Vinhas de Souza and Philippe De Lombaerde (eds.), The Periphery of the Euro: Monetary and Exchange Rate Policy in CIS Countries. Ashgate. Aldershot, U.K., pp. 313-46.
- Search Google Scholar
- Export Citation
)| false Leheyda, Nina, 2006. Determinants of Inflation in Ukraine: A Cointegration Approach. In ( Lúcio Vinhas de Souzaand Philippe De Lombaerde eds.), The Periphery of the Euro: Monetary and Exchange Rate Policy in CIS Countries. Ashgate. Aldershot, U.K., pp. 313- 46.
Lissovolik, Bogdan, 2003. Determinants of Inflation in a Transition Economy: The Case of Ukraine. IMF Working Papers 03/126, International Monetary Fund.
Mafi-Kreft, Elham, and Steven Kreft, 2006. Importing Credible Monetary Policy: A Way for Transition Economies to Fight Inflation? Economics Letters Vol. 92, No. 1, pp. 1-6.
Ohnsorge, Franziska, and Nienke Oomes, 2004. Inflation, Money Demand, and De-Dollarization. IMF Country Report No. 04/316, pp. 10-42, International Monetary Fund.
Pelipas, Igor, 2006. Money Demand and Inflation in Belarus: Evidence from Cointegrated VAR. Research in International Business and Finance Vol. 20, No. 2, pp. 200-14.
Rodríguez Palenzuela, Diego, Gonzalo Camba-Méndez, and Juan Ángel Garcia, 2003. Relevant Economic Issues Concerning the Optimal Rate of Inflation. European Central Bank Working Paper No. 278.
Rogoff, Kenneth, 2003. Globalization and Global Disinflation. Economic Review—Federal Reserve Bank of Kansas City Vol. 88, No. 4, pp. 45-79.
Roodman, David, 2006. How to Do xtabond2: An Introduction to “Difference” and “System” GMM in Stata. Working Paper 103. Center for Global Development.
Schiff, Jerald Alan, Philippe Egoumé-Bossogo, Miho Ihara, Tetsuya Konuki, and Kornélia Krajnyák, 2006. Labor Market Performance in Transition: The Experience of Central and Eastern Europe. IMF Occasional Paper No. 248.
Shiratsuka, Shigenori, 1999. Measurement Errors and Quality-Adjustment Methodology: Lessons from the Japanese CPI. Economic Perspectives Vol. 23, No. 2, pp. 2-13.
Siliverstovs, Bosiss, and Olena Bilan, 2005. Modeling Inflation Dynamics in Transition Economies: The Case of Ukraine. Eastern European Economics Vol. 43, No. 6, pp. 66-81.
Stock, James H., Jonathan H. Wright, and Motohiro Yogo, 2002. A Survey of Weak Instruments and Weak Identification in Generalized Method of Moments. Journal of Business and Economic Statistics Vol. 20, No. 4, pp. 518-29.
Vdovichenko, Anna G., and Victoria G. Voronina, 2006. Monetary Policy Rules and their Application in Russia. Research in International Business and Finance Vol. 20, No. 2, pp. 145-62.
Kiel Institute and International Monetary Fund. We would like to thank our colleagues at the IMF and the Kiel Institute, in particular Albert Jaeger, Alex Hoffmaister, Franziska Ohnsorge, Man-Keung Tang, and Edda Zoli, for helpful comments. All remaining errors are our own.
See http://www.imf.org/external/np/rosc/rosc.asp for details on CPI statistical techniques used in Russia, Ukraine, Belarus, and Moldova. Moldova does not follow international standards for proper techniques in imputation of missing and new observations. To the extent missing observations are associated with scarcity of an item in question, this may understate the CPI, which would imply the inflation differential is understated.
See Rodríguez Palenzuela, Camba-Méndez, and Garcia (2003) for a full discussion of factors affecting the choice of optimal inflation rate. See Cukierman (1992) for a discussion of the various motives that may impinge on a central banks’ inflation choice. Besides employment, these can include fiscal revenues, external competitiveness and financial stability.
The short-run trade-off will depend, among other things, on the variance of nominal relative to real shocks (but not directly on the level of inflation). Thus a sustained attempt by a transition country central bank to exploit the output-inflation trade-off would essentially eliminate it. For this reason, we confine our sample to the post-hyperinflation period. More generally, when the game between the central bank and agents is in an equilibrium, there is no further incentive for the central bank to shock the economy with unanticipated inflation, and thus to change the relative variances. What matters then are other structural influences on the trade-off, which help determine the level of inflation at which the incentive disappears. We model these.
Technical factors may constrain a central bank’s choice of monetary regime. However, those central banks which lack the capacity to manage a flexible exchange rate regime are not doomed to import an inflation process; they can always manage inflation via an adjustable peg.
In transition economies, structural changes—obsolescence of capital and disorganization on one side of the transition recession and massive productivity gains on the other—are likely to have been much more important than cyclical issues over the last 10 years. For these reasons it is difficult to estimate the output gap or other capacity measures for these economies, and indeed data in these areas is very incomplete. Our variables for structural unemployment pressures are thus reasonable controls for capacity pressures.
Other authors like Cukierman, Edwards, and Tabellini (1992) argue that the agricultural sector is difficult to tax and therefore consider it to be a fiscal motive. This interpretation makes some sense for developing economies with low revenue ratios and large informal agricultural sectors. For the transition economies which we consider, where the agricultural sector is much more organized (e.g., collective farms) and where tax ratios are generally in the 30–40 percent of GDP range, it is not a very compelling interpretation.
Existing empirical evidence suggests that if anything this should work against an inflation differential. Égert, Halpern, and MacDonald (2006) suggest that among the CEEC the highest Balassa-Samuelson effect may be found in Hungary and Poland (up to 2 percent) and the lowest in the Czech Republic and Latvia (close to zero). Égert (2005) finds the effect to be 0.7 percent for Russia and for 0.5 percent for Ukraine.
Many of the transition economies have had large contingent liabilities at one point or another. The so-called lost savings in the CIS from the early 1990s hyperinflation are an example. These liabilities would provide an additional incentive towards inflation, since these have typically not been indexed. Data limitations preclude their use.
If all prices are raised in proportion to the exchange rate depreciation, there would be no real depreciation, and no incentive to use this channel. This could occur in a fully dollarized economy, but none of the transition economies fits this mold for the time period in question.
Financial dollarization is one reflection of financial market development that could impact inflation outcomes, for instance by creating an incentive for a central bank to minimize exchange rate movements (this would prevent impacts on agents’ balance sheets, but would also transmit external disturbances to the economy). However, dollarization can also reflect expectations of inflation (see Levy Yeyati, 2006), and due to this endogeneity issue, is not modeled here.
Up-to-date data on central bank independence is in any event unavailable. IMF staff reports on Article IV consultations (Bassett 2003; IMF 2005b; 2005c; 2006) as well as the assessments by the Economist Intelligence Unit (EIU 2005; 2006) suggest that central bank independence is still lacking in the CIS-West.
Other unanticipated demand shocks could come via the government (unforeseen and rapid fiscal loosening), or via consumers and investors (unrelated to terms-of-trade gains, and showing up in large unexpected capital inflows). Given lags in fiscal policy formulation and implementation, we do not see unanticipated fiscal shocks as a key issue. Given our annual data, we would also expect monetary policy to be able to react to slower-to-materialize consumption and investment shocks, leaving in practice a small unanticipated component.
Since average political stability in Russia, Ukraine, Belarus and Moldova does not differ greatly from average political stability in central and eastern European states, the analysis of the gap is not materially effected by using the more parsimonious model as a baseline.
We do not find interest or exchange rate smoothing to be important influences. These results are available on request from the authors.
All dependent variables are treated as strictly exogenous, since in other specifications the number of instruments exceeds the cross section dimension. The Arrelano-Bond test (not reported) indicates that all the dynamic panel regressions are free of serial correlation.
Using the actual inflation gap has no impact on the relative importance of the explanatory variables.